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Class Statistics

  • Presentation

    Presentation

    Statistics provides methods for collecting, organising, describing, analysing and interpreting data used in market research, consumer behaviour, customer segmentation, campaign evaluation and sales analysis. In the field of marketing, these methods enable data to be transformed into information that supports the formulation, implementation and evaluation of strategies.   In this module, students develop the skills to apply descriptive and inferential statistical techniques to the analysis of marketing problems, interpret quantitative results, identify patterns and relationships between variables, and support decisions based on empirical evidence.
  • Code

    Code

    ULHT168-194
  • Syllabus

    Syllabus

    Basic applications in Statistics; Data collection and sampling; Measures of Descriptive Statistics; Data organization: graphs and tables; Probabilities; Introduction to Statistical Inference; Linear correlation and linear regression.
  • Objectives

    Objectives

    The course aims to develop data analysis skills, enabling students to apply statistical techniques to solve marketing problems. At the end of the course, students should be able to: Understand and calculate measures of central tendency, dispersion, percentiles, quartiles, deciles, and distribution measures. Use descriptive statistical methods, both numerical and graphical, to interpret data sets. Recognize and apply basic probability concepts in problem solving. Calculate fundamental parameters such as mean deviation, variance, and standard deviation. Understand and apply concepts of correlation and linear regression in practical contexts. Analyse and apply hypothesis tests, including Student's t-test, to compare means and support data-driven decision-making.
  • Teaching methodologies

    Teaching methodologies

    Problem-Based Learning (PBL). With this approach, the program aims to engage students in purposeful learning experiences, encouraging them to tackle authentic and relevant challenges of the present. Students are prompted to apply critical thinking throughout the investigative process. This methodology fosters essential skills for both academic and professional contexts, enhancing their learning journey.
  • References

    References

    Agresti, A., Franklin, C. A., & Klingenberg, B. (2021). Statistics: The Art and Science of Learning from Data, Global Edition. Bispo, R., & Maroco, J. (2005). Estatística Aplicada às Ciências Sociais e Humanas. 2a Edição. Climepsi Editores. Barroso, M., Sampaio, E., & Ramos, M. (2010). Exercícios de Estatística Descritiva para as Ciências Sociais. 2a Edição. Edições Silabo. Healey, J. F., & Donoghue, C. (2020). Statistics: A Tool for Social Research and Data Analysis. Cengage Learning. Mazzocchi, M. (2008). Statistics for marketing and consumer research. SAGE. Murteira, B., Ribeiro, C. S., Silva, J. A., & Pimenta, C. (2023). Introdução à Estatística. 4a Edição. Escolar Editora. Reis, E., Melo, P., Andrade, R., & Calapez, T. (2021). Estatística Aplicada (volume 1). 7a Edição. Edições Sílabo.  
  • Assessment

    Assessment

     

    Descrição

    Ponderação

    Exercícios

    10%

    Primeira frequência

    40%

    Segunda frequência

    50%

     

     

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